Dairy cows - dual-flow continuous culture
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA943156 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR23800218.fastq.gz | Fastqsanger.gz | |||
| SRR23800219.fastq.gz | Fastqsanger.gz | |||
| SRR23800220.fastq.gz | Fastqsanger.gz | |||
| SRR23800221.fastq.gz | Fastqsanger.gz | |||
| SRR23800222.fastq.gz | Fastqsanger.gz |
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Project description:In this study, samples of 16 dairy cows from a MAP infected farm were used. Serum, milk and fecal samples were collected. Categorizing these cows into two groups based on their MAP infection status different standard methods for detection MAP were applied. Healthy controls showed no positive results in enzyme-linked immunosorbent assay (ELISA) with serum and milk samples (cattletype MAP Ab, Qiagen, Hilden, Germany; In-direct, IDVet, Grabels, France) and after cultivation of fecal samples on commercial Her-rold´s Egg Yolk Agars (HEYM agar, Becton Dickinson, Heidelberg, Germany) for 12 weeks. Cows with positive results were grouped into MAP infected cows. Specifically, for mass spectrometry analysis serum of seven MAP infected cows and seven healthy controls were used. All animals were from the same farm and were kept under the same environmental conditions. For additional mass spectrometry analysis with a further control group sam-ples of 21 dairy cows from an uninfected farm were examined. All cattle from this farm showed negative results in ELISA with serum and milk samples. Additionally, there was never a positive result in regularly tested fecal samples and sock swab samples of this farm. For verification of differential CTSS expression in Western blot analysis five dairy cows from another infected farm were consultedincluded. MAP status of these cows was analyzed by cultivation of fecal samples on HEYM agar for 12 weeks and ELISA with se-rum samples. In detail, two cattle were categorized into healthy controls and three cattle into MAP infected cows. Withdrawal of bovine venous whole blood and experi-mental protocols were approved by the local authority, Government of Upper Bavaria, permit no. ROB-55.2-2532.Vet_03-17-106.
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Project description:The transition to lactation challenges dairy cows metabolically. Immune dysfunction and infectious disease risk is the hallmark of this transition period. Transcriptome data of PBMC shows differentially expressed pathways postpartum. Metabolically stressed cows show upregulation of innate immune pathways and inflammation.
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Project description:M. Berg, J. Plöntzke, S. Leonhard-Marek, K.E. Müller & S. Röblitz. A dynamic model to simulate potassium balance in dairy cows. Journal of Dairy Science 100, 12 (2017).
High-performing dairy cows require a particular composition of nutritional ingredients, adapted to their individual requirements and depending on their production status. The optimal dimensioning of minerals in the diet, one being potassium, is indispensable for the prevention of imbalances. Potassium balance in cows is the result of potassium intake, distribution in the organism, and excretion, and it is closely related to glucose and electrolyte metabolism. In this paper, we present a dynamical model for potassium balance in lactating and nonlactating dairy cows based on ordinary differential equations. Parameter values were obtained from clinical trial data and from the literature. To verify the consistency of the model, we present simulation outcomes for 3 different scenarios: potassium balance in (1) nonlactating cows with varying feed intake, (2) nonlactating cows with varying potassium fraction in the diet, and (3) lactating cows with varying milk production levels. The results give insights into the short- and long-term potassium metabolism, providing an important step toward the understanding of the potassium network, the design of prophylactic feed additives, and possible treatment strategies.
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Project description:This article contains raw and processed data related to research published by Swartz et al. [1]. Proteomics data from liver of postpartum dairy cows were obtained by liquid chromatography-mass spectrometry following protein extraction. Differential abundance between liver of cows experiencing either negative energy balance (NEB, n=6) or positive energy balance (PEB, n=4) at 17±3 DIM was quantified using MS1 intensity based label-free. There is a paucity of studies examining the associations of NEB with the liver proteome in early lactation dairy cows. Therefore, our objective was to characterize the differences in the liver proteome in periparturient dairy cows experiencing naturally occurring NEB compared to cows in PEB. In this study, multiparous Holstein dairy cows were milked either 2 or 3 times daily for the first 30 days in milk (DIM) to alter energy balance, and were classified retrospectively as NEB (n=18) or PEB (n=22). Liver biopsies were collected from 10 cows (n=5 from each milking frequency), that were retrospectively classified according to their energy balance (NEB, n=6; PEB, n=4). The liver proteome was characterized using label-free quantitative shotgun proteomics. This novel dataset contains 2,741 proteins were identified, and 68 of those were differentially abundant between NEB and PEB (P≤0.05 and FC±1.5); these findings are discussed in our recent research article [1]. The present dataset of liver proteome can be used as either biological markers for disease or therapeutic targets to improve metabolic adaptations to lactation in postpartum dairy cattle.
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